Search published articles


Showing 2 results for Bijari
Relationship between body image and self-efficacy in female students of Hamadan University of Medical Sciences
Shohreh Emdadi, Sahar Bijari, Fatemeh Rostami, Ziba Bagheri Sahamishoar, Majid Barati, Maryam Farhadian,
Volume 8, Issue 2 (Volume 8, Number 2 2017)
Abstract

Background and Aim: Body image is one of the main factors of self efficacy. This study aimed to investigate the relationship between body image and self-efficacy among female students in Hamadan University of Medical Sciences.

Methods: This cross-sectional study was carried out on 408 female students of Hamadan University of Medical Sciences in 2017 with a stratified sampling method. To gather data, we used Multidimensional Body Self-Relation Questionnaire (MBSRQ) and general self-efficacy questionnaire and recorded demographic variables. Data were analyzed with SPSS-21 software using Pearson correlation and linear regression tests.

Results: The dimensions of body areas satisfaction and illness orientation were evaluated at relatively desirable and moderate levels, respectively. Students' self-efficacy was also estimated at 60.05% of the mean score of the maximum achievable score at the moderate level. The results of regression analysis showed that the dimensions of the illness orientation, overweight preoccupation, fitness orientation, self-classified weight and appearance evaluation predicted the self-efficacy among the female students. In total, different dimensions of body image explained 14.1% of the variance of self-efficacy.

Conclusion: We suggest providing training packages about body image dimensions improvement to enhance the self-efficacy of university female students.


Applications of artificial intelligence in wound management: a review
Alireza Sadeghi Moghaddam Bijari, Hoda Keshmiri Neghab, Mohammadhasan Soheilifar,
Volume 16, Issue 3 (Volume 16, No 3 2025)
Abstract
The treatment of wounds has historically been a significant challenge in medicine, incurring substantial financial and emotional costs for both governments and patients. Consequently, researchers have continuously sought novel methods to enhance the wound healing process. In recent years, with the advancements in computer science and the emergence of Artificial Intelligence (AI), many professional fields, including medical sciences, have undergone transformations. There has been a general effort to utilize AI as an assistant or even a human replacement in certain processes. In the field of wound care, the application of AI-based tools is expected to improve the speed and accuracy of the treatment system, leading to faster wound healing and better outcomes for patients.
AI has been presented in various models, each operating on different datasets and employed in diverse research studies. Both software and hardware tools based on AI have been designed and introduced in several investigations. Their performance has been evaluated at various levels, from laboratory to clinical settings, and their efficacy has been demonstrated.
Based on the findings, it can be stated that AI can provide effective assistance to clinical and research staff in the diagnostic, therapeutic, and educational processes of wound treatment. In some cases, it may even reduce the need for direct clinical staff involvement for patients.
Page 1 from 1     

© 2026 , Tehran University of Medical Sciences, CC BY-NC 4.0

Designed & Developed by : Yektaweb